Cytotoxicity of Gold Nanoparticles

Cytotoxicity of Gold Nanoparticles

C H A P T E R E L E V E N Cytotoxicity of Gold Nanoparticles Yu Pan, Matthias Bartneck, and Willi Jahnen-Dechent Contents 225 227 228 230 230 232 23...

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C H A P T E R

E L E V E N

Cytotoxicity of Gold Nanoparticles Yu Pan, Matthias Bartneck, and Willi Jahnen-Dechent Contents 225 227 228 230 230 232 233 236 239

1. 2. 3. 4.

Introduction Dosage and Quantification of Gold Nanoparticles Aggregation State of Nanoparticles in Fluids Cell-Based Nanotoxicity Studies 4.1. Cytotoxicity 4.2. Cell cycle arrest and proliferation inhibition 4.3. Cell death 4.4. Oxidative stress References

Abstract Nanomaterials are now routinely used in technical as well as medical applications. The very physicochemical properties that favor nanomaterial application are the prime cause that these materials cannot be considered “generally safe.” We are still far from predicting the toxicological profile of new nanoparticles, despite continuous attempts to establish a structure–function relation between the physical and chemical properties of nanoparticles and their interactions with biological systems. Herein, we summarize some basic concept to assess nanoparticle toxicity, death pathways, cell cycle, and oxidative stress in response to nanoparticle exposure of cells.

1. Introduction Nanotechnology is an expanding branch of material sciences. Nanomaterials have a high surface to volume ratio, possess quantum size effects, and are different from their bulk form in many respects (Schmid et al., 1999). Favorable optical, mechanical, and electronic properties of materials in the nanoscale allow novel applications in high-technology and biomedical

Helmholtz Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany Methods in Enzymology, Volume 509 ISSN 0076-6879, DOI: 10.1016/B978-0-12-391858-1.00012-5

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2012 Elsevier Inc. All rights reserved.

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science. These altered properties together with their small size, which is on a similar scale like biological macromolecules, may cause nanomaterials to directly affect biological systems, whereas the same compound in bulk form may be inert and nontoxic. Therefore, the risk assessment of nanomaterials is indispensable for safe and sustainable nanotechnology development. Nanoparticles have been shown to influence biological systems in many ways. The size of nanoparticles determines their cellular uptake, endocytosis, cytotoxicity, biodistribution, and clearance pathway (Chithrani et al., 2006; De Jong et al., 2008; Hirn et al., 2011; Pan et al., 2007; Semmler-Behnke et al., 2008; Sonavane et al., 2008). The hydrodynamic diameter of nanoparticles is particularly important in determining the nano–bio interaction (Choi et al., 2007a, 2011). Quantum dots with identical metallic core size, but with anionic or cationic charges (dihydrolipoic acid, cysteamine) had a higher tendency to bind serum proteins, thus increasing the hydrodynamic diameter compared to those with zwitterionic and neutral surface layers. An increased hydrodynamic diameter hinders renal clearance. Prolonged retention of nanoparticles in organisms can thus cause adverse effects. Apart from the size effect, the surface properties of nanoparticles, including charge, ligand density, and hydrophobicity have been shown to control the bio–nano interactions as well (Chompoosor et al., 2010; Harush-Frenkel et al., 2008; Lipka et al., 2010). Nanoparticles with cationic surfaces have a high cellular uptake, high toxicity, and renal clearance rate compared to those with an anionic surface. The most intensively studied cases are the increased uptake rate and toxicity of nanoparticles modified with positively charged polyethyleneimine (PEI) and cell-penetrating peptides. These modifications were met with enhanced cytotoxicity because of membrane damage. The bio–nano interface is crucial in nanotoxicity (Nel et al., 2009). Bio–nano interface reactions affect the size and surface properties of the nanoparticles after binding with solute components in biological fluids (proteins, glycans, and ions) and thus alter the uptake pathways (nonspecific and receptor-mediated). Conversely, bio–nano interactions may change the protein composition in biological fluids, the activity and distribution of the biological molecules in the organism, and they may constitute or reveal hidden immune epitopes. Improved understanding of nanoparticle toxicity will help to avoid adverse effects and may also assist in designing nanoparticles. In many cases, a suitable surface modification may render toxic nanoparticles less toxic to allow application in medical therapy. The situation we are currently confronting, however, is an enormous amount of newly emerging nanoparticles. To meet this demand, high-throughput and cost-efficiency, and animal welfare-friendly methods are required to obtain integral toxicity data from thousands of different nanoparticles. Cell-based tests are undoubtedly the most widely applied screening method. The toxicity of nanoparticles is commonly expressed as the concentration causing 50% of growth inhibition in cell culture (IC50). Results derived from cell tests are used to derive a reasonable dose for the initial animal experiments.

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A growing body of toxicity studies using a wide variety of nanoparticles (TiO2 ( Johnston et al., 2009; Long et al., 2007), Au (Pan et al., 2009), ZnO (Heng et al., 2011; Xia et al., 2008), Ag (AshaRani et al., 2009; Xu et al., 2012), SiO2 (Ye et al., 2010), Fe3O4 (Naqvi et al., 2010), carbon nanotubes (Srivastava et al., 2011), Al2O3 (Dey et al., 2008)) has shown that the production of reactive oxygen species (ROS) is a common mechanism causing nanoparticle toxicity. It has been pointed out that the toxicity of nanoparticles is determined by their potency to produce ROS, which is balanced by the antioxidant capacity of an organism to prevent oxidative damage (Nel et al., 2006). A modest increase of oxidative stress can be usually rescued by a corresponding increase in the cellular reducing capacity. Continuous accumulation of oxidative stress, however, triggers irreversible cell death. The addition of glutathione and N-acetyl-cysteine, which enhances the antioxidant capacity of the organism reduce greatly the toxicity of, for example, ultrasmall gold nanoparticles (AuNPs; Pan et al., 2009). To this end, methods to measure and quantify cellular oxidative stress in response to nanoparticles will be described. Cell-based toxicity tests are a mere starting point for toxicity studies. The interaction between different cell types and the dynamic translocation, distribution, sedimentation, and clearance of nanoparticles in living animals (Lasagna-Reeves et al., 2010; Minchin, 2008; Schleh et al., 2012; SemmlerBehnke et al., 2008; Sun et al., 2005), and the organ-specific toxicity together with the metabolic response in the presence of nanoparticles can only be revealed in animal tests. Therefore, it is of great importance to test nanoparticle toxicity in rodent models as early in the study as possible. Many nanoparticles under study are designed specifically for in vivo applications. The size and surface are optimized to allow tissue and cell entry, and even to bind specific targets (Choi et al., 2007b; Felsenfeld et al., 1996; Giordano et al., 2009; Hainfeld et al., 2006; Pissuwan et al., 2006; Sperling et al., 2008). Therefore, in vivo tests should be done in a vertebrate model capable of basic human organ functions.

2. Dosage and Quantification of Gold Nanoparticles The dose makes the poison. This principle of toxicology was expressed five centuries ago by Paracelsus and equally pertains to nanomaterials. The dosage of nanoparticles in toxicology research, therefore, should cover the full concentration range from nontoxic to cytotoxic. The toxicity should then be reported as the concentration at which half-maximum toxicity is observed— the inhibitory concentration 50 (IC50). We strongly encourage readers to experimentally determine the molar concentration of gold contained in their nanoparticles and to use equimolar doses to compare the toxicity of various AuNPs. The common practice of using particle concentration is fraught with

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error, because polydispersity of the particles and their tendency to aggregate renders particle number virtually meaningless. By contrast, [Au] can be verified with great accuracy, both before and after compound addition to cells. Methods to quantify AuNPs in stock solution, in biological fluids, and in organ extracts include high-sensitivity methods including neutron activation analysis (NAA) and inductively coupled plasma mass spectrometry (ICP-MS). Table 11.1 lists several published methods to quantify AuNPs and to study their biodistribution.

3. Aggregation State of Nanoparticles in Fluids Nanoparticles will only behave as nanomaterials as long as they maintain their small size. Aggregating nanoparticles will progressively behave like bulk material. Close attention should therefore be given to the interaction of nanoparticles and biological fluids, which might greatly influence toxicity. The composition of biological fluids was shown to alter the particle size, surface characters, endocytosis pathway, intracellular trajectory, and the toxicity profile of the nanoparticles. On the other hand, nanoparticles can alter the nature of bioactive proteins depending on size, shape, surface charge, and curvature (Nel et al., 2009). Commonly used media include cell culture medium (with or without serum), phosphate buffered saline (PBS), 0.9% sodium chloride, plasma, and whole blood. Many nanoparticles will aggregate in saline and serum free medium because of the salt content of these solutions. Addition of serum can, to some extent, improve the stability of the nanoparticles in biological fluids by forming a protein halo or corona (Nel et al., 2009). Serum protein binding may alter the biological activity of nanoparticles in more ways than aggregation. Many proteins will facilitate AuNP endocytosis by a process called opsonization. In addition, AuNPs may inhibit coagulation factors and decrease the free fibrinogen content of serum. Binding may be pH-dependent by design as in the “intelligent nanomaterials” meant for drug release at sites of inflammation, which have a lower pH than healthy tissue (Tsai et al., 2011). Nanoparticle binding works both ways in that the particles collect molecules from the surrounding fluid but also bind to macromolecular assemblies or cell surfaces. Ultrasmall AuNPs approach the size of typical protein ligands and may inadvertently activate cell surface receptors. AuNPs are particularly notorious for binding thiol ligands because of the high electronegativity of Au and the electropositivity of sulfur. Thus, AuNP will preferentially bind sulfur containing compounds and may deplete the glutathione-based redox buffering capacity of biological fluids. Methods to measure the actual size of nanoparticles in fluids after contact with the protein are dynamic light scattering (DLS), small angle X-ray

Table 11.1 Methods to quantify nanoparticles in biological samples Methods

Sample material

Sensitivity

Data

References

TEM

Cell, tissue

High

Goel et al. (2009)

ICP-MS ICP-AES NAA

Cell, tissue Cell, tissue Cell, tissue

Verify the uptake of AuNPs Quantitative Quantitative Quantitative

UV/vis AAS Silver enhancement

Nanoparticles Cell, tissue Cell, tissue

Spectroscopic photoacoustic

Living mouse

Photoacoustic tomography

Living rat

CT

Living swine

Liquid scanning transmission electron microscopy

Living cells

Lasagna-Reeves et al. (2010) Chithrani et al. (2006) Lipka et al. (2010), Semmler-Behnke et al. (2008) Low Semiquantitative Cho et al. (2011) 0.8–1.88 mg/kg Quantitative Kattumuri et al. (2007) 400 mg Au/mouse Semiquantitative, Kim et al. (2011) localization 400 mg Au/mouse Semiquantitative, Kim et al. (2011) localization 0.8  109 nanocages/g Semiquantitative, Yang et al. (2007) body weight localization 86–99 mg/kg Semiquantitative, Boote et al. (2010) localization 1.8 nM, 2 h Semiquantitative, Peckys and de Jonge (2011) localization High High 10–100 mg/kg

TEM, transmission electron microscopy; ICP-MS, inductively coupled plasma mass spectrometry; ICP-AES, inductively coupled plasma atomic emission spectroscopy; NAA, neutron activation analysis; AAS, atomic absorption spectroscopy; UV–vis, ultraviolet–visible spectroscopy; CT, X-ray computed tomography.

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scattering (SAXS), size-exclusion chromatography (SEC), isothermal titration calorimetry (ITC), and surface plasmon resonance (SPR). In addition, fluorescence quenching measurement may be used to study nanoparticle– protein interaction. The emission properties of the aromatic residues in proteins (tryptophan, tyrosine, and phenylalanine) and fluorescence quenching by AuNPs of fluorophore probes were employed to study nanoparticle– protein interaction. Applying this method, Lacerda and colleagues showed that the binding kinetics between AuNPs and serum proteins is strictly sizedependent. Bigger particles had a higher tendency to bind proteins (Lacerda et al., 2010). Protein conformation changes in contact with nanoparticles were recently reviewed (Fei and Perrett, 2009).

4. Cell-Based Nanotoxicity Studies Cell-based assays measure cell morphology, proliferation, viability, toxicity, motility, and production of metabolites. Compared to toxicity testing in animals, cell-based assays are relatively easy and low cost, and the dose of testing compound can be precisely defined. Immortalized cell lines like HeLa cells are commonly used to compare the cytotoxicity of nanoparticles varying in size and surface chemistry (Pan et al., 2007). One disadvantage of immortal cell lines is that their genome and the proliferation pattern deviate from normal healthy cells. This drawback is remedied by using primary cells, which are, however, generally harder to obtain and to grow and should therefore be used for specific purposes only. In addition, the role of nanoparticles in the differentiation of stem cells may be studied by in vitro cell tests (Ferreira et al., 2008; Yi et al., 2010).

4.1. Cytotoxicity Cell morphology is an excellent parameter reflecting the status of cells in response to nanoparticles. Thus, time-lapse movies of cells recorded at low light phase-contrast greatly help in determining appropriate time points for further detailed investigations. Viability and membrane integrity are measured using the cell impermeable stain, trypan blue, or Hoechst 33258, or propidium iodide (PI), or measuring the mitochondrial reducing capacity with 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT). Furthermore, assessment of the intracellular ATP level and the release of the intracellular enzyme lactate dehydrogenase (LDH) into the culture medium are also measured as proxies of cell integrity. Commercial assays employ colorimetric or fluorogenic substrates to measure metabolic activity and cell integrity. For medium to high throughput, these assays may be run in a multiplex format using robotic pipetting platforms

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(Ferreira et al., 2011). Fluorescence assays may, however, be unsuitable to assay the toxicity of nanoparticles, because many particles, especially small AuNPs, quench fluorescence, and thus cause false negative readings. We have found the MTT assay presented in Protocol I to be simple, cheap, fast, and reliable for toxicity testing of metallic nanoparticles with a wide range of ligands. 4.1.1. Protocol I 4.1.1.1. Cell viability tests using MTT The cells are commonly seeded in 96-well plates. For immortal cell lines like HeLa cells, the seeding density relies on the cell proliferation rate. As a rule of thumb, 90% confluence (30,000–40,000 cells) in untreated controls should be reached at the end of the incubation. A proliferation curve should be recorded for every cell line to identify the growth stages and the proliferation rate of the cells. We have noted earlier that cells differ in their sensitivity to toxic compounds depending on the growth phase of the cell culture. Cells in the logarithmic growth phase are more sensitive than those in the stationary phase (Pan et al., 2007). Our routine method for measuring AuNP toxicity in HeLa cells is as follows: (1) Two thousand cells are seeded in each well and are incubated for 72 h in 96-well plates. (2) The supernatant is replaced with 100 ml fresh medium containing different concentrations of nanoparticles. The cells are incubated for another 48 h. (3) Ten microliters of PBS containing 5 mg/ml MTT is dispensed to each well. The plates are incubated for 2 h. After incubation, the yellowish water-soluble tetrazolium is chemically reduced to a water-insoluble purple formazan product by viable cells engaged in oxidative metabolism. Thus, metabolic activity serves as a proxy of cell number and viability. (4) The water-insoluble formazan is dissolved in a solvent mixture (100 ml) consisting of isopropanol (80 ml) with hydrochloric acid (0.04 mM ) and 3% sodium dodecyl sulfate (20 ml). (5) Absorption of the samples is measured with a plate reader at 595 nm. Triplicate wells are set in each plate and three independent experiments are required to determine the IC50. (6) IC50 values are calculated using a four parameter logistic equation. Data are plotted as a sigmoidal dose–response curve with variable slope using statistics software, for example, GraphPad Prism. For each material, the IC50 values are determined from triplicate wells. IC50 values are routinely repeated in three independent experiments with almost identical results. The osmolality, pH, and the reducing capacity of the nanoparticles at the highest testing concentration should be recorded prior to the cytotoxicity measurement. The exposure length should be longer than one proliferation cycle of the cells. We routinely expose the

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cells to the nanoparticles for 48 h before the MTT test. A positive MTT test can be confirmed by observing the formazan accumulation inside the mitochondria. The cells will appear speckled in bright field microscopy. Interference of AuNPs on the colorimetric reading in the MTT test is prevented, because the supernatant containing AuNPs is replaced by an organic solvent. This washing step minimizes the false-positive photometric reading derived from AuNPs in MTT-based viability tests (Fig. 11.1).

4.2. Cell cycle arrest and proliferation inhibition Most viability assays are end point tests. A low number of viable cells can be due either to increased cell death or to a low proliferation rate. Nanoparticles can affect cell proliferation in both directions, inhibiting (Kalishwaralal et al., 2011; Karthikeyan et al., 2010) and enhancing (Unfried et al., 2008). Cell-cycle control is critical for normal growth and development. AuNPtriggered loss of cell cycle control in somatic cells may potentially cause inflammation and even tumor formation. This is especially important because many nanoparticles under study are designed as antitumor agents. The assessment of cell cycle arrest in the presence of nanoparticles is therefore indispensable to understand their antitumor mechanisms. Staining of cells with carboxyfluorescein succinimidyl ester (CFSE), 5-bromo-20 deoxyuridine (BrdU) incorporation, and DNA content measurements are commonly used to study the proliferation of cells treated with nanoparticles. The cell cycle comprises four distinct phases (G1 phase, S phase, G2 phase, and mitosis), and two checkpoints (G0/G1 and G2/M checkpoints), which assure that no DNA damage is transmitted to daughter cells. Nuclear DNA is duplicated during the synthetic or S phase. The cell cycle stage of a given cell can thus be determined by measuring the DNA amount.

% Survival

100 75 50

Au1.4MS Au1.8MS

25 0

−2

−1

0

1

2

3

4

Log concentration (mM)

Figure 11.1 Representative sigmoidal dose-response curves showing the cytotoxicity of ultrasmall AuNPs. The cytotoxicity of AuNP of 1.4 and 1.8 nm gold core diameter, respectively, were tested during the logarithmic growth phase of HeLa cells. The IC50s of Au1.4MS and Au1.8MS are 46 and 230 mM, respectively.

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Cell proliferation arrest of the cells will be reflected in the DNA content and a changed G1 and G2 ratio. Glucose capped AuNPs have been shown to sensitize prostate cancer cells toward radiotherapy by inducing a G2/M growth arrest (Roa et al., 2009). PI is a fluorescent molecule that binds to DNA in a stoichiometric manner and is commonly used to analyze the cellular DNA content or ploidy (Suzuki et al., 1997; Watson et al., 1987). Hoechst 33342, Hoechst 33258, and 40 ,6-diamidino-2-phenylindole (DAPI) are alternative DNA stains. After excitation at 488 nm, PI emits red fluorescence that can be detected with a 562–588 nm band pass filter. Fluorescence intensity is directly proportional to the amount of DNA. Cells in the G1 and M phases have half of the DNA content compared to cells in the S and G2 phases. Thus, cells in G1 phase have a weaker fluorescence intensity compared to those in G2 phase (Bedner et al., 1999; Moore et al., 1998). An additional advantage of PI-based DNA content measurement is that apoptosis can be simultaneously detected as an additional sub-G1 peak and the broadening of the G1 peak, both reflecting apoptosis-related DNA fragmentation. 4.2.1. Protocol II 4.2.1.1. Measuring DNA content to determine the cell cycle phase (1) Cells are seeded in 6-well plates and incubated for 72 h prior to the addition of nanoparticles. (2) The supernatant is replaced with 100 ml fresh medium containing nanoparticles. Cells are further incubated for the required period. All cell-material combinations are set up in triplicates. (3) After the nanoparticle incubation, cells are trypsinized and rinsed with PBS. (4) Washed cell pellets are fixed in cold 70% ethanol at 4  C for 60 min. (5) After fixation, cells are washed with PBS and resuspended in 250 ml PBS. RNAse (250 ml, 1 mg/ml) and PI (500 ml, 0.1 mg/ml) are added at room temperature for 15 min or overnight at 4  C in the dark. (6) 20,000 cells are analyzed using a FACSCalibur or FACSCanto or a comparable flow cytometer and the CELLQuest software (BectonDickinson) (Fig. 11.2).

4.3. Cell death Apoptosis, autophagy, necroptosis, aponecrosis (Formigli et al., 2000), and necrosis are major cell death pathways that have been described in great detail (Peter, 2011). They differ with regards to trigger, timing, degree of regulation, and key regulators. Nevertheless, there is considerable overlap, and for practical purposes we confine ourselves to discriminate between apoptosis (slow, regulated, energy dependent—regulated cell death), and necrosis (fast, not energy dependent—unregulated cell death/cell lysis). Cell

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650 2N (G1)

Counts

520

390

260

DNA fragments

4N (G2)

Sub G1

130

0 100

101

102

103

104

Propidium iodide

Figure 11.2 Representative flow cytometry diagram of DNA content measurement with propidium iodide staining. Untreated cells (black curve) show a minor peak of propidium iodide (PI) fluorescence at 1.05  103 depicting 4N cellular DNA content (G2 phase, about 20% of cells) and a major peak of fluorescence at 8  102 indicating 2N cellular DNA content (G1 phase, 70% of the cells). Cells staining intermediary reside in S phase. When the HeLa cells are treated with staurosporine (light gray line) to trigger apoptosis, the relative proportion of cells in G2 phase increases to 50% indicating a G2/ M block of the cells. Together with the sub G1 peak and the low fluorescent peak indicating DNA fragments this pattern is typical of apoptosis.

death is a dynamic process (Loos and Engelbrecht, 2009), and time-lapse video microscopy using low light phase contrast illumination once again is very helpful to estimate morphological changes in response to nanoparticles. The microscope used for time-lapse video capture is equipped with a heat plate and CO2 supply. Apoptotic cells will round up and will show shrinkage of the cytoplasm, blebbing of the plasma membrane, and nuclear condensation (Ziegler and Groscurth, 2004). A rapid cytoplasmic swelling is usually seen in necrotic cells. The membrane lipid phosphatidylserine externalizes from the inner leaflet of the cell membrane to the outer leaflet in the early stage of apoptosis. By using fluorescent annexin V, which specifically binds phosphatidylserine, the number of cells undergoing apoptosis can be quantified. This experiment is usually performed in combination with PI staining to estimate the percentage of necrotic and secondary necrotic cells. PI is membrane impermeable and thus will only enter cells with a damaged cell membrane to stain their nucleus. Caspases and B-cell lymphoma 2 (BCL2) family proteins are major executors of apoptosis. Measuring the activity of these enzymes is useful to detect apoptosis, and

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to identify the death mechanism. Furthermore, attenuation of caspase enzymes by inhibitors is known to prevent apoptosis but not necrosis. The general caspase inhibitor, Z-VAD-fmk, which binds to the catalytic site of caspase proteases efficiently prevents the induction of apoptosis, and thus may be employed to verify that death pathway. DNA fragmentation is another hallmark of apoptosis. The activation of caspase-activated DNase (CAD) causes cleavage of nuclear DNA into fragments of 180 bp a late event in apoptosis. Therefore, “DNA laddering” is diagnostic of apoptotic cells. The DNA fragmentation can be detected either by gel electrophoresis or by flow cytometry-based DNA content measurement, as described above (Herrmann et al., 1994). The terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assay detects DNA cleavage sites that are abound in apoptotic cells. The TUNEL assay is thus also commonly used to detect apoptosis. 4.3.1. Protocol III 4.3.1.1. Determination of apoptosis versus necrosis Annexin V and PI are double-staining probes for apoptosis by detecting the externalization of phosphatidylserine and membrane integrity. The apoptotic cells externalize their phosphatidylserine early in apoptosis when the cell membrane is still intact. Therefore, the early apoptotic cells have a positive annexin V, but a negative PI signal. In contrast to apoptotic cells, necrotic cells lose membrane integrity and both annexin V and PI will penetrate the leaky cell membrane to stain intracellular phosphatidylserine (annexin V) and nuclear DNA (PI). The test cannot discriminate between apoptotic cells at the late stage (secondary necrosis) and necrotic cells. Thus, time course measurements are required to determine the cell death pathway. (1) Cells are seeded into 6-well plates (HeLa 40,000 cells/well) and incubated for 72 h at 37  C with 5% CO2 prior to the addition of nanoparticles. The seeding density is adjusted depending on the growth rate of the cell lines used and on the incubation duration. At least 20,000 cells are required at the end of the experiment to allow cell analysis by flow cytometry in the untreated samples. (2) After 72 h of incubation, nanoparticles at the desired concentrations are applied. (3) After the exposure to the nanoparticles, the supernatant containing detached apoptotic or necrotic cells together with the trypsinized cells are collected and washed twice with binding buffer followed with the addition of fluorescein isothiocyanate (FITC)-labeled annexin V. (4) Annexin V binding to phosphatidylserine is calcium dependent. Therefore, the binding buffer must contain 2.5 mM calcium chloride throughout all steps including washing.

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(5) The cells are incubated at room temperature for 15 min. Thereafter, an aliquot of the PI stock solution (10 ml, 50 mg/ml) is added to each well, and cells are further incubated for 5 min before one final wash in binding buffer. For each experiment, untreated cells serve as a negative control and cells incubated for 24 h with staurosporine (0.2 mM) serve as a positive control for apoptosis. Twenty thousand cells are counted for each sample by flow cytometry. Results are analyzed by CELLQuest software (Becton-Dickinson) (Fig. 11.3).

4.4. Oxidative stress Oxidative stress is considered one of the most salient features of nanoparticle toxicity (Nel et al., 2006). A low level of oxidative stress can be counteracted by the cellular antioxidant defense mechanisms. A moderate level of ROS can initiate inflammatory pathways by activating the NF-kB pathway. Excessive production of ROS will oxidize cellular components including the cell membrane lipids, protein, and DNA and will lead to cell death (Murphy et al., 2011). Current mechanisms of ROS generation include protein conformation changes caused by nanoparticle binding that entail the so-called unfolded protein response (Wiseman et al., 2010), mechanical cell damage induced by nanoparticles, and direct interaction between the nanoparticle metal and oxygen species (Fenton and Haber-Weiss reaction). Little is known about the direct production of ROS by nanoparticles. Methods commonly used to detect oxidative stress can be grouped as follows: 1. The first class of methods measures the accumulation of intracellular ROS (hydroxyl radicals, superoxide anion, hydrogen peroxide, peroxyl radical) by oxidation of the fluorescent probe, 5-(and-6)chloromethyl-20 ,70 -dichlorodihydrofluorescein diacetate, acetyl ester (CM-H2DCFDA). CM-H2DCFDA is cell permeable and becomes fluorescent when the dihydrofluorescein is oxidized to fluorescein by intracellular ROS. 2. The increase of intracellular ROS is accompanied by the structural and functional changes of mitochondria, commonly summarized as permeability transition (PT) (Murphy and Steenbergen, 2011). Analysis of mitochondrial integrity is therefore well suited to estimate the cellular energy production states, and the extent of the damage. Membrane permeable cationic fluorescent probes (e.g., JC-1) are commonly used for this purpose. JC-1 accumulates along the mitochondrial potential (Dc) in mitochondria of healthy cells. At high concentrations, JC-1 dimerizes and emits red fluorescence. Upon PT, the mitochondria become leaky and release JC-1 into the cytoplasm where it fluoresces green as a monomer.

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B

Untreated

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Propidium iodide

0.2 µM staurosporine

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AnnexinV-FITC

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C 4

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Propidium iodide

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Figure 11.3 Flow cytometric determination of living, apoptotic, and necrotic HeLa cells treated with test compounds. Cells are scored for annexin V/PI double staining to estimate the relative amounts of live cells (annexin V/PI double negative, bottom left quadrant), apoptotic cells (annexin V-positive/PI-negative, bottom right quadrant), and necrotic cells (annexin V/PI-double positive, top right quadrant), respectively. The percentages of cells are given for each quadrant. (A) HeLa untreated, (B) HeLa 0.2 mM staurosporine, 24 h, (C) HeLa 110 mM Au1.4MS, 48 h.

3. Measuring oxidized biomolecules is an alternative method to detect oxidative stress. Commonly measured oxidized biomolecules include peroxidized lipids (malondialdehyde, 4-hydroxynonenal, and 8-iso-prostaglandin; Sevanian and Hochstein, 1985), peroxynitrite (Pryor and Squadrito, 1995), and oxidized DNA derivatives (8-hydroxydeoxyguanosine, 8-oxo-7, 8-dihydroguanine; Dizdaroglu et al., 2002).

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4. The fourth commonly used method for oxidative stress measurement, which adapts well to both in vitro and in vivo models measures the antioxidant capacity of the cell or organism. The best-studied antioxidant measurements include superoxide dismutase, catalase, glutathione peroxidase, glutathione, and ascorbic acid. In addition to the four methods listed above, few studies have directly measured ROS, and thus oxidative stress, by electron paramagnetic resonance (EPR; Shulaev and Oliver, 2006). 4.4.1. Protocol IV 4.4.1.1. Measuring oxidative stress We measure ROS using CMH2DCFDA, because it is both inexpensive and reliable. (1) HeLa cells are seeded in 6-well plates at initial densities of 40,000 cells in 2 ml and further incubate for 72 h.

200 2

Counts

160

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4

1 3

80

40

0 100

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102 CM-H2DCFDA

103

104

Figure 11.4 CM-H2DCFDA revealing the accumulation of reactive oxygen species. Cells growing under the normal condition had no reactive oxygen species and the major population settle between 100 and 101 (curve 2). Treatment with 0.3% H2O2 for 30 min induced strong accumulation of intracellular ROS and the cell population shifted to much strong signal around 101–103 (curve 4). The Au1.4MS induced cellular oxidative stress. The number of unstressed cells (100–101) decreased while a second peak occurred between 101 and 103 (curve 3), which indicates the accumulation of the reactive oxygen species. N-Acetyl cysteine reduced the ROS (curve 1) induced by Au1.4MS and the majority of cells shifted back to the level of untreated cells (100–101).

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(2) Fresh medium containing nanoparticles are added to the cells. All cellmaterial combinations are set up in triplicates. (3) At the end of the incubation, cells are trypsinized and rinsed with PBS. (4) After rinsing, cells are suspended in a buffer containing CM-H2DCFDA. For cell assays, the stock solution is diluted in PBS to a final working concentration of 2.5 mM. Treatment of cells with 0.3% H2O2 for 30 min serves as a positive control for oxidative stress. (5) Twenty thousand cells are analyzed using FACSCalibur or FACSCanto flow cytometers and the CELLQuest software (Becton-Dickinson) (Fig. 11.4).

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